Forward Deployed Engineer Manager

Accenture; Madrid; Presencial; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

Accenture is seeking a Forward Deployed AI Engineer to embed with client teams and drive real-world AI deployment. You will own outcomes such as time-to-value, adoption, reliability, and scalability across multi-stakeholder environments, bridging pilot success to scalable capability.

You will work across a broad tech stack, shaping AI reinvention strategy for CTO/CFO/CISO levels and delivering reusable blueprints to scale AI programs across client engagements.

Formación

• Strong engineering background with cloud-native architectures (APIs, microservices, containerization, serverless).
• Experience designing agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production.
• Expertise with AI platforms (OpenAI, Claude, Vertex AI) and multi-provider pipelines.
• Proven ability to lead software engineering teams and own delivery in client-embedded contexts.

Responsabilidades

• Lead enterprise AI platform deployments across complex client environments, owning architecture to adoption.
• Own programme-level delivery outcomes: time-to-value, reliability, adoption velocity, scalability with metrics.
• Lead rapid experimentation to produce production systems within days or weeks.
• Architect and govern enterprise AI solutions across identity, data, security, governance, platform, and workflows.
• Shape reinvention strategy for client leadership with value architecture and ROI roadmaps.
• Publish reusable reinvention blueprints and accelerators for cross-engagement scalability.
• Lead architecture design sessions and executive workshops with client leadership.
• Codify delivery learnings and engineering standards to evolve the practice.

Conocimientos

Cloud-native systems

APIs

Microservices

Containerization

Serverless

Agentic solutions design

RAG workflows

OpenAI

Vertex AI

Stakeholder management

Team leadership

Descripción del empleo

Role Description

This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments.Youown outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes.

The market is beginning to understand what leading technology companies havedemonstrated: AI products fail not because the models are weak but because deployment is broken. The gap between a successful AI pilot and an AI capability that scalesisbridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role.

Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.

Key Responsibilities

• Lead enterprise AI platform deployments across complex multi-stakeholder client environments — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — owning the fullprogrammefrom architecture through adoption
• Ownprogramme-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple concurrent workstreams, with commercial metrics attached
• Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments
• Architect and govern enterprise AI solutions across the full technology stack: identity, data, security, governance, platform layer, and multi-system workflow integration atprogrammescale
• Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use caseprioritisationframeworks, and multi-year AI adoption roadmaps
• Define and publish reusable reinvention blueprints, patterns, and accelerators that scale across multiple client engagements and grow the FDE practice
• Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite leadership teams
• Codify delivery learnings, failure patterns, and engineering standards that shape the FDE practice and enable the next generation of forward deployed engineers

Basic Qualifications

• Strong engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Expertisein designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Strong experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• Strong experience leading software engineering teams: overseeing delivery,allocatingresources across workstreams, and owning the professional development of direct reports"
• Demonstrated end-to-end delivery ownership in a client-embedded environment, internal projects, vendor labs, or team-only deployments do not qualify
• Proven ability to articulate business value: can quantify the impact of deployments in terms a CFO would recognize and act on
• Experience presenting to and building trust with senior client stakeholders, CTO, CFO, or CISO level
• Non-linear profiles are expected and welcomed, assessment is based ondemonstrateddeployment experience and outcome ownership, not CV pattern matching
• People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations